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	Treatment of mustard tuber wastewater (MTWW) using a pilot-scale packed cage rotating biological contactor system: process modeling and optimization 期刊论文 OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 页码: 9 作者: Dong, Yang; Chen, Youpeng; Guo, Jinsong; Wang, Jianhui; Yan, Peng \| 收藏 \| 浏览/下载：34/0 \| 提交时间：2021/08/20 Biological nutrients removal Biofilm Response surface methodology Disks rotating speed Removal maximum Energy assessment
	Plasma-arc technology for the thermal treatment of chemical wastes 会议论文 OAI收割 26th Annual International Conference on Incineration and Thermal Treatment Technologies, IT3, Phoenix, AZ, United states, May 14, 2007 - May 18, 2007 作者: Sheng HZ(盛宏至) 收藏 \| 浏览/下载：18/0 \| 提交时间：2017/06/01 Amorphous glass Arc technologies Average temperature Chinese Academy of Sciences Cooling speed Destruction and removal efficiency Emission limits Experimental facilities Graphite crucibles Hazardous elements Hazardous wastes Maximum temperature Molten state Numerical simulation Organic wastes Production process Pyrolysis process Research institutes Sichuan , China Solid residues Sub-systems Thermal treatment Velocity field
	A new approach for the removal of mixed noise based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：35/0 \| 提交时间：2013/03/25 This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light and indeed we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm the tracing of WTMM is not just tedious procedure computationally algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.